On Inequality-Sensitive and Additive Achievement Measures Based on Ordinal Data

This paper, following earlier work on the measurement of inequality when only ordinal information is available, proposes an axiomatic derivation of a new class of inequality-sensitive and additive achievement measures. Use is then made of these indices to study health achievement in Europe, using information on self-assessed health in 30 countries, based on the European Health Interview Survey (wave 2).     

Assessing measurement errors in the CDM research–innovation–productivity relationships

ABSTRACT

The Crépon-Duguet-Mairesse 1998 article, known as CDM, initiated a structural econometric framework to analyze the relationships among research, innovation and productivity, which has been estimated most generally on the basis of cross-sectional innovation survey-type data. Some econometric implementations of the CDM approach have suggested that such data give useful but imprecise measures of the innovation output (share of innovative sales), and to a lesser degree of the innovation input (R&D). These ‘measurement errors’ may result in attenuation biases of the estimated R&D and innovation impact elasticities in the two basic CDM ‘roots’ relations of R&D to innovation and innovation to productivity, as well as in the extended production function à la Griliches linking directly R&D to productivity. Using a panel of three waves of the French Community Innovation Survey (CIS), we assess these biases and the magnitude of the underlying measurement errors, assuming mainly that they are ‘white noise’ errors. We do so by comparing two pairs of usual panel estimators (Total and Between) in both the cross-sectional and time dimensions of the data (Levels and Differences). We find large measurement errors on innovation output in the innovation–productivity equation, resulting in large attenuation biases in the related elasticity parameter. We also find smaller but sizeable measurement errors on R&D, with significant attenuation biases in the corresponding elasticity estimates, in the R&D–innovation equation and the extended production function. Simulations suggest that the measurement errors on innovation and R&D are unaffected by similar measurement errors on the capital variable.     

Implementation of the revenue-maximizing auction by an ignorant seller

In a general auction framework with independent private values, we propose a game, with a simple economic interpretation, that allows to implement the revenue-maximizing auction outcome when the seller ignores the distributions of the different bidders’ valuations. In this detail-free implementation procedure, an ascending-price contest is organized and the winner volunteers a payment to the seller; this payment can then be challenged by another bidder who knows the distribution of the winner’s valuation.Received: 4 June 2003, Accepted: 4 April 2005, We have benefited from comments by seminar participants at the Econometric Society North American Winter Meeting and European Meeting, PURC University of Florida, University of Wisconsin, as well as by two referees and an Associate Editor. The authors also wish to acknowledge the hospitality of IDEI in Toulouse where they started this research. The second author acknowledges the financial support of CRSHC, CIRANO and the Bell University Labs.